Cigarette addiction is the leading cause of preventable death in our nation. Despite the life-threatening health consequences of smoking and the substantial heavy economic burden on society, close to 25% of the population continues to smoke. Two major factors contribute to continued smoking and relapse: craving elicited by smoking cues (SCs) and craving elicited by nicotine withdrawal (WD). Inability to combat WD-induced craving, which declines within a month, plays a major role in EARLY relapse. However, smokers report that SCs can trigger relapse months or even years after quitting. Existing smoking cessation medications alleviate WD and/or reduce nicotine reward, and are helpful for subgroups of smokers. However, other 'cue-vulnerable' smokers receive less benefit evincing the critical need to identify agents that target SC reactivity. A number of factors, including genetic variance, may underlie the relative contribution of SCs and WD to susceptibility to relapse. Indeed, we have found a profound effect of variance in the dopamine transporter SLC6A3 (DAT) gene on SC reactivity. Our findings are consistent with the well-established role of dopamine (DA) in drug reward and drug-associated cues. GABA B agonists modulate DA and have shown promise as drug cue blocking agents. Evidence suggests that the GABA B agonist, baclofen modulates drug seeking and taking behavior and thus may be a 'prototypical probe' to examine the effects of GABA B agonists on SC reactivity. The goal of this proposal is to identify a SC-vulnerable pharmaco-responsive endophenotype. Towards this goal, we will: AIM 1, confirm a SC-vulnerable endophenotype mediated by variance in functional DA-modulating candidate genes AIM 2, utilize our innovative brain/behavioral/genetic paradigm to link 'baclofen-induced' neural responses during SC exposure with behavioral correlates to identify a pharmaco-responsive endophenotype~ and Exploratory AIM: explore the interaction between allelic variance in DA-modulating genes and baclofen- induced brain and behavioral responses. Our model will employ the quantitative technique of perfusion fMRI, which facilitates the measurement of medication-induced (longitudinal) neural modifications, both in the brain 'at rest' and during cognitive and emotional tasks. Thus, we will acquire resting baseline and SC exposure data in smokers prior to and following a 3-week medication regimen. Smoking behavior will be monitored using 'novel naturalistic methods'. DNA samples will be analyzed for allelic variance in DA-regulating genes. Ultimately, the goal for contemporary medicine is to establish brain/behavioral/genetic endophenotypes that predict medication response, such that treatments are tailored to manage individual vulnerabilities (i.e., Personalized Medicine). The proposed studies will provide knowledge about genetic influences and GABA agonist mechanisms on a major relapse predictor: SC reactivity. This will have a sustained and lasting impact on smoking treatment strategies and will aid in meeting a major goal set by NIDA, which is to Eradicate Tobacco Abuse and Addiction.